EP2296364B1

EP2296364B1 - Methods and system for improved color characterization

Info

Publication number: EP2296364B1
Application number: EP10176089.0A
Authority: EP
Inventors: Juan Liu; Haitham Hindi; Lalit K. Mestha; Kenneth J. Mihalyov
Original assignee: Palo Alto Research Center Inc; Xerox Corp
Current assignee: Palo Alto Research Center Inc; Xerox Corp
Priority date: 2009-09-11
Filing date: 2010-09-10
Publication date: 2017-07-26
Anticipated expiration: 2030-09-10
Also published as: US20110063631A1; US8390885B2; EP2296364A3; JP2011061784A; JP5525392B2; EP2296364A2

Description

BACKGROUND

The present disclosure is generally related to the field of color rendering devices such as image/text printing or display systems and to methods and systems for characterizing color output devices, such as color displays, printers and printing devices thereof. Characterization of the underlying mapping (forward transform) from a printer or display's internal device dependent color space (e.g., CMY, CMYK, RGB, etc.) to a perceived print-out color space (e.g., La*b* or other device independent color space) is important to achieving color consistency within and across color reproduction devices. In practice, this color mapping varies from device to device, and over time in a single device, due to physical conditions such as temperature, humidity, inks or other marking materials, printed media type (e.g., paper stock type, thickness), component wear and tear, and manufacturing tolerances associated with the reproduction devices. The characterization of the forward color mapping facilitates adjustments in the rendering process via control algorithms to adjust individual devices in order to achieve color consistency across product lines and over time. Conventional forward transform characterizations utilize either physics-based or data-fitting models. Physics-based modeling is based on the physical aspects of the printing/rendering device, such as the xerographic process and the half-toning pattern used, whereas data-fitting techniques measure color patches created from various CMYK values, and a mapping is created based on the input and output data values. Data-fitting models are employed by either interpolating nonparametric lookup tables or evaluating parametric analytical functions that fit the data. In general, however, the accuracy of nonparametric models is dependent upon the number of data points used in the initial characterization, and thus cost considerations may limit the extent to which a given device is characterized accurately. Moreover, adapting such models over time is cost prohibitive. Parametric modeling, which somewhat more cost effective with respect to computational overhead, is often unable to accurately characterize all aspects of a device's performance.
US 2009/0086292 A1 describes L*a*b* scanning using RGB-clear. Systems and methods are described that facilitate reducing metamerism in a scanner or printer system by evaluating and manipulating unfiltered clear channel information. Using a four channel model to predict CIE XYZ tristimulus values from RGB and clear, a linear model is generated based on a polynomial matrix conversion. For example, one such model has cocefficients weighting I, R, G, B, W, R², G², B², W², RG, RB, RW, GB, GW, BW, and corresponding third order terms. The XYZ values predicted by the linear model are converted to L*a*b*, and compared with measured L*a*b* values. A statistic involving the difference between measured and computed L*a*b* values is used as a metric in a non-linear optimization to obtain the best values for the matrix elements. Once the matrix is optimized, it is employed for printer calibration, error detection, and the like.
US 2004/0165199 A1 describes a calibration method for an imaging device. A method includes forming a plurality of test patches in an array of orthogonal rows. The test patches are formed by using at least one printhead in an imaging machine. Each of the test patches is associated with a respective one of a plurality of initial input color values. The array of test patches includes a plurality of rows of varied-input test patches and at least one row of first equivalent-input test patches. A respective output color value of each of the test patches is measured. At least one first mathematical relationship is generated based on the output color values of the at least one row of first equivalent-input test patches. A plurality of adjusted input color values are calculated for respective ones of the varied-input test patches. Each adjusted input color value is calculated based upon the generated at least one first mathematical relationship. A second mathematical relationship is computed between the adjusted input color values and the output color values. The imaging machine is calibrated by using the second mathematical relationship.
US 2008/0239344 A1 describes color printer characterization or calibration to correct for spatial non-uniformity. Methods and systems are presented for calibrating or characterizing a color printer or determining the color response of a color printer to combat spatial non-uniformity, in which color patches are printed on a test page according to an input matrix of input color in a printer-dependent-color space and the test page is measured to provide a corresponding output matrix of output color in a printer-independent-color space. Initial forward and inverse color transforms between the input and the output colors are generated based on the input and the output matrices. The output values are mapped to the input color space based on the initial inverse transform to form a feedback matrix, and spatial non-uniformities present in the printed test page are estimated according to noise values derived from the input matrix and the feedback matrix. The input matrix is modified according to the estimated spatial non-uniformity to form a modified input matrix of input color, and final forward and inverse transforms are generated for the color printer according to the modified input matrix and the output matrix.

SUMMARY OF THE INVENTION

It is the object of the present invention to improve color characterization of color reproduction devices. This object is achieved by providing a method of characterizing a color reproduction device according to claim 1 and a color processing device according to claim 11. Embodiments of the invention are set forth in the dependent claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The present subject matter may take form in various components and arrangements of components, and in various steps and arrangements of steps. The drawings are only for purposes of illustrating preferred embodiments and are not to be construed as limiting the subject matter.

Fig. 1 is a flow diagram illustrating an exemplary method for characterizing a color reproduction device in accordance with the present disclosure;
Fig. 2 is a simplified schematic system level diagram illustrating an exemplary multi-color document processing system in accordance with several aspects of the disclosure;
Fig. 3 is a detailed side elevation view illustrating an exemplary embodiment of the system of Fig. 2 in accordance with the present disclosure;
Fig. 4 is a flow diagram illustrating a color printer device characterization embodiment of the present disclosure;
Fig. 5 is a flow diagram illustrating an exemplary color printer characterization adaptation embodiment of the present disclosure; and
Fig. 6 is a schematic diagram illustrating further details of the characterization system in the embodiments of Figs. 2 and 3.

DETAILED DESCRIPTION

Referring now to the drawings, the present disclosure provides for decomposition of a forward device color mapping surface into a smooth surface represented as a parametric model, such as a low order polynomial regression in one example, as well as a high-frequency residual, for example, represented as a lookup table for interpolation of the fine features of the mapping. The inventors have appreciated that the component transform parts are influenced by different aspects of the printing physics and have different time evolution properties. In particular, the inventors have recognized the smooth surface of the device mapping modeled in parametric fashion varies over time whereas the residual portion represented in nonparametric form remains generally static. Decomposition of the device forward transform into parametric and nonparametric components facilitates achieving estimation accuracy comparable to conventional data-fitting techniques, together with computational efficiency and a significantly smaller number of data samples in the color space for adaptation. In addition, the technique yields robustness to noise and varying printing conditions. The device characterization systems and methods of the disclosure are illustrated and described below in the context of exemplary printing systems having marking stations for application of marking material (e.g., ink, toner, etc.) to printable media, as well as display devices that render visible images on a display screen, although the characterization concepts of the present disclosure may be applied to any type of color reproduction device capable of producing visible images.
Fig. 1 illustrates an exemplary method 2 for characterizing a color reproduction device, and Figs. 2, 3, and 6 depict exemplary printing systems or devices 100 with system controllers 122 and characterization systems 124 in which the method 2 may be implemented. While the exemplary method 2 of Fig. 1 and the processes 200, 300 in Figs. 4 and 5 below are illustrated and described in the form of a series of acts or events, it will be appreciated that the various methods of the disclosure are not limited by the illustrated ordering of such acts or events except as specifically set forth herein. In this regard, except as specifically provided hereinafter, some acts or events may occur in different order and/or concurrently with other acts or events apart from those illustrated and described herein, and not all illustrated steps may be required to implement a process or method in accordance with the present disclosure. The illustrated methods 2, 200, 300 and other methods of the disclosure may be implemented in hardware, processor executed software, or combinations thereof, whether in a single characterization system or in distributed form in two or more components or systems, in order to characterize a color printing device, color display or other color reproduction device, and may be employed in any form of printing system including without limitation desktop printers, computers, network printers, stand-alone copiers, multi-function printer/copier/facsimile devices, high-speed printing/publishing systems and digital printing presses, digital cameras, etc. wherein the disclosure is not limited to the specific applications and implementations illustrated and described herein.
Referring to Figs. 1 and 6, the method 2 begins at 10 in Fig. 1, where a plurality of visible color images 162 are produced (e.g., color patches 162 printed onto page(s) 160 or rendered on a display 123 in Fig. 2) according to an input initial characterization data set 122a (Fig. 6) using a color reproduction device 100, 123 (Figs. 2 and 3). In one embodiment, the data set 122a is C,M,Y,K data representing given amounts of Cyan, Magenta, Yellow, and black (K), although different embodiments can utilize other device dependent color data that constitute an internal representation of color for the specific device 100. At 20, the color images 162 are measured (e.g., using a scanner 126 in Fig. 2) to generate a measured initial characterization data set 124a (Fig. 6). In the illustrated examples, the scanner 126 senses the visible patch images 162 of the printed page(s) 160 or the images 162 rendered on the display 123 and generates corresponding L, a*, and b* data values in a CIE (Commission Internationale de L'eclairage) color space in which L defines lightness, a* corresponds to a red/green value, and b* denotes the amount of yellow/blue, although other measured color data may be generated by the sensor in other second color spaces which include values representing the physical appearance of the spectral content of the generated images as perceived by human viewers in other embodiments.
At 30 in Fig. 1, the input initial characterization data set 122a and the measured initial characterization data set 124a are used to provide two mappings of the color reproduction performance of the device 100. At 32, a parametric forward color transform 125a is generated using the input initial characterization data set 122a and the measured initial characterization data set 124a. In one embodiment, this is accomplished by fitting a second or third-order polynomial surface to the initial data set, wherein the transform generation at 32 yields a number of polynomial parameters or coefficients 125a (Fig. 6) that are stored in the characterization system 125. Once the parameters are established, mapping a given C,M,Y,K value in the first color space to a predicted L,a*,b* value in the second color space can be done by evaluating the corresponding polynomials for the L, a*, and b* values using the coefficient parameters 125a generated at 32.
At 34, an estimated initial characterization data set 124b is generated using the parametric forward color transform 125a and the input initial characterization data set 122a. In one embodiment, this is done by evaluating values of the input initial characterization data set 122a using the parametric forward color transform 125a to generate the estimated initial characterization data set 124b. A nonparametric forward color transform 125b (Fig. 6) is generated at 36 using the measured and estimated device independent color values in the second color space for the initial color characterization set 122a and 124a. This may be done, for example, by subtracting the estimated initial characterization data set values 124b from the measured initial characterization data set values 124a to determine residual difference values. The forward color transform 125 for the device 100 is then constructed at 40 using the parametric and nonparametric forward color transforms 125a and 125b. In one embodiment, the forward color transform 125 for the device 100 is constructed at 40 as a summation of the parametric and interpolated nonparametric forward color transforms 125a, 125b.
Certain embodiments of the process 2 may also provide for adapting the parametric forward color transform 125a at 50 in Fig. 1. In this regard, the selective decomposition into the parametric and nonparametric components 125a and 125b, respectively, provides for efficient updating or adaptation of only the smooth surface parametric component transform 125a to accommodate device performance drifts over time. At 52, a plurality of visible adaptation images 162 are produced at 52 according to an input adaptation data set 122b in the first color space (Figs. 2 and 6) using the color reproduction device 100. As with the initial color characterization, the adaptation images may be printed as color patches (e.g., patches 162) on a printed sheet or may be rendered on the display 123. The visual adaptation images 162 are then measured at 54 (e.g., via scanner 126) to generate a measured adaptation data set 124c in the second color space (Fig. 6), and the parametric forward color transform 125a is adapted or modified at 56 using the input and measured adaptation data sets 122b and 124c, such as by adjusting the polynomial surface based on the adaptation data. In a preferable implementation, the scanner 126 or other measurement means is an in-line apparatus integrated into the device being characterized and the adaptation process 50 may be automated to run without user intervention.
Referring now to Figs. 2, 3, and 6, the exemplary color processing device 100 includes a rendering system with xerographic stations 102 and a display 123, either or both of which operate to produce visible images according to input color data in the first space. The device 100 further includes a system controller 122 which provides input color data (e.g., C,M,Y,K) to the rendering system 102, 123 according to a print job 118, as well as a scanner type sensor 126 that generates (e.g., L,a*,b*) data 124a, 124c representative of the printed or displayed visible images 162 in the second space. The scanner 126 in certain embodiments may be integrated into the rendering system for in-line scanning of printed images 162 on pages 160. Fig. 2 illustrates an exemplary tandem multi-color document processing system 100, where the marking devices 102 are individually operable according to control signals or data from the controller 122 to transfer toner marking material 151-153 onto an intermediate substrate 104 that may or may not be a photoreceptor, in this case, a shared intermediate transfer belt (ITB) 104 traveling in a counter clockwise direction in the figure past the xerographic marking devices 102, also referred to as marking engines, marking elements, marking stations, etc. In other embodiments, a cylindrical drum may be employed as an intermediate transfer substrate, with the marking devices 102 positioned around the periphery of the drum to selectively transfer marking material thereto.
Fig. 3 depicts a system 100 having four marking devices 102 configured along a shared or common intermediate transfer belt 104. This figure shows an exemplary printing environment or system 200 including an embodiment of the above-described document processing system 100 having marking stations 102 along with a transfer station 106, a supply of final print media 108, and a fuser 110 as described in Fig. 2 above. In normal operation, print jobs 118 are received at the controller 122 via an internal source such as an in-line or outboard scanner 126 (Fig. 2) and/or from an external source, such as one or more computers 116 connected to the system 100 via one or more networks 124 and associated cabling 120, or from wireless sources. The print job execution may include printing selected text, line graphics, images, magnetic ink character recognition (MICR) notation, etc., on the front and/or back sides or pages of one or more sheets of paper or other printable media 108. In this regard, some sheets 108 may be left completely blank in accordance with a particular print job 118, and some sheets may have mixed color and black-and-white printing. Execution of the print job 118, moreover, may include collating the finished sheets 108 in a certain order, along with specified folding, stapling, punching holes into, or otherwise physically manipulating or binding the sheets 108. In certain embodiments the system 200 may be a stand-alone printer or a cluster of networked or otherwise logically interconnected printers, with each printer having its own associated print media source 108 and finishing components including a plurality of final media destinations, print consumable supply systems and other suitable components. Alternatively the system may include multiple marking engines 102 with a common media supply 108 and common finishers that are configured either serially or in parallel (separate parallel paper paths between feeding and finishing).
The system 100 in Figs. 2, 3, and 6 includes a characterization system 124 that is operatively coupled with (and may be implemented integrally to) the system controller 122. In one exemplary embodiment, the characterization system 124 is implemented as a processor-based system having suitable processing and memory components programmed or configured to implement the characterization process 2 and other functionality as described herein. The characterization system 124 may be operated generally according to the process 2 above to cause the rendering system 102, 123 to produce a plurality of visible color images 162 according to an input initial characterization data set 122a in a first color space. The system 124 receives a measured initial characterization data set 124a in a second color space representative of the color images 162 from the sensor 126, and generates the parametric forward color transform 125a using the input initial characterization data set 122a and the measured initial characterization data set 124a. The system 124 generates the estimated initial characterization data set 124b using the parametric transform 125a and the input initial characterization data set 122a, for example, by evaluating the values of the input initial characterization data set 122a using the parametric forward color transform 125a. The system 124 then generates the nonparametric forward color transform 125b using the measured and estimated initial characterization data sets 122a, 124a, and constructs the forward color transform 125 for the device 100 using the parametric and nonparametric forward color transforms 125a and 125b. Thereafter, the characterization system 124 adapts the nonparametric forward color transform 125a to compensate for drift effects in the system 100, such as during startup processing, periodically, or at other intervals in automated and/or user-initiated fashion.
Referring now to Figs. 4 and 5, a detailed implementation of a characterization process 200 and a corresponding adaptation process 300 are hereinafter described in the context of color printer characterization in the system 100. The color reproduction performance of the system 100 is characterized in this case as a mapping from the four-dimensional C,M,Y,K first color space representation of the input data to a three-dimensional L,a*,b* representation of the perceivable spectral content of generated images in a second (device independent) CIE color space, and thus involves formation of three functions, one for each of the second color space values, i.e., the estimated color (L, a*, b*) = (f_L(C, M, Y, K), f _a* (C, M, Y,K), f _b* (C,M, Y,K). The system controller 122 in certain embodiments is configured to use this forward transformation to derive an inverse transform by which the input data from print jobs 118 can be modified such that the output images (printed or displayed) are consistent when viewed by users across different printers and over time. The decomposition of the forward transform 125 into two elements (parametric 125a and nonparametric 125b in Fig. 6) advantageously facilitates scalability so that the transform does not require a huge number of training samples as well as computational efficiency allowing quick calibration and easy adaptation, robustness against noise and robustness against printing condition variations.
The partition decomposes the overall mapping 125 (f_L , f _a*, or f_b* ) into low-frequency and high- frequency components 125a, 125b, where the low-frequency part 125a is a smooth surface which can be modeled using a parametric function by parametric estimation or other data-fitting techniques. The high-frequency component 125b is modeled using a more flexible nonparametric representation. With respect to printing systems generally, the inventors have appreciated that the two components of the transform represent different aspects and exhibit different time-evolution patterns. The smooth surface represented by the parametric transform 125a is related to the internal operating conditions of the color reproduction device, such as temperature, toner mass-charge ratio, and other physical characteristics that vary over time. Consequently, the modeled smooth surface f_surf (transform 125a) drifts slowly, and is therefore advantageously adapted over time in certain embodiments of the characterization system 124. The fine-level details of the non-parametric transform f_residual (transform 125b), on the other hand, are largely a function of printer design and external factors such as halftone patterns and printing media 108 (e.g., glossy paper vs. flat paper, heavy-weight vs. regular paper), and thus remain generally static. The system 124 constructs the residual transform f _residual 125b for representative external conditions. Consequently, the two-part separation allows a computationally efficient adaptation scheme in which f _surf 125a and f _residual 125b are adapted separately or differently over time. In this regard, the nonparametric transform f _residual 125b is initially more expensive to construct, but does not require subsequent adaptation because it is static, whereas the low-frequency parametric transform f _surf 125a drifts overtime, and is therefore advantageously adapted from time to time, but the adaptation is quick and low-cost, because the transform f _surf 124a is modeled as a polynomial surface with relatively few parameters. This allows frequent update of the surface, e.g., once per day or even per hour, or during startup, etc.
The process 200 in Fig. 4 illustrates the initial device characterization beginning at 202, in which a C,M,Y,K input initial characterization data set 122a is provided at 204. In one example for an 8-bit C,M,Y,K space, the data set 122a is homogeneously sampled with respect to a regular 16×16×16×16 grid in the first color space, in which each of the C,M,Y,K dimensions is a uniform 16-level grid taking values in the range from 0 to 255. Color patches (e.g., patches 162 on page(s) 160 in Fig. 2) are then printed at 206 according to the input initial characterization data set 122a. The color patches 162 are then scanned at 208 to generate the measured initial characterization La*b* data set 124a. From the input initial characterization C,M,Y,K data set 122a and the measured initial characterization La*b* data set 124a, the characterization system 124 constructs f _surf 125a at 210 by fitting a 2^nd or 3^rd order polynomial surface to the data, although any order of parametric fitting may be employed. In one implementation, fitting a smooth surface to obtain the parametric transform f _surf 125a is done via regression. For instance, a 2^nd order surface over the four-dimensional C,M,Y,K space is parameterized by 15 parameters 125a, and a 3^rd order surface has 45 parameters 125a. With the estimated parameters 125a (f_surf(C,M,Y,K) specified), the system 124 can evaluate the estimated surface value for any given CMYK input. The parametric forward color transform 125a in this example is f_L,surf (CMYK); f _a*,surf(CMYK); and f _b*,surf(CMYK).
At 212 in Fig. 4, the characterization system 124 generates estimated La*b* data values for each location in the 16x16x16x16 grid of the C,M,Y,K first color space by evaluating the parametric forward color transform 125a for each data value of the input initial characterization C,M,Y,K data set 122a to generate the estimated initial characterization set 124b (Fig. 6). At 214, the system 124 computes the difference between the measured and estimated La*b* values to generate the nonparametric forward color transform 125b: $f_{L, residual} (CMYK) = L (CMYK) - f_{L, surf} (CMYK);$
$f_{a *, residual} (CMYK) = a * (CMYK) - f_{a *, surf} (CMYK);$
and $f_{b *, residual} (CMYK) = b * (CMYK) - f_{b *, surf} (CMYK) .$
The nonparametric transform f _residual 125b in one embodiment is evaluated via nonparametric interpolation. In this case, for the CMYK values of the 16-level grid set, a residual value is stored in a lookup table of the transform 125b. For any CMYK value not on the grid, a distance-averaged interpolation technique is employed in this embodiment to evaluate f_residual to find its immediate neighbors in the input initial characterization set and their corresponding residual La*b* values. Next, the system 124 computes a weighted average of the neighbors' La*b* values according to the following formula: $f_{residual} (C, M, Y, K) = \sum_{i \in N} a_{i} f_{residual} (i),$

where N is the neighborhood in the core set CMYK space, and f _residua/ (i) is the residual value of the neighboring point that can be looked up from the data set. Each neighbor i is weighted by a weight αi, set to be proportional to the inverse distance to the neighbors in the CMYK space. In this manner, a neighbor point closer in the CMYK space is given a heavier weight than the neighbors further away. The weighted average is then taken to be the predicted value of the La*b* residual. This grid-based residual representation 125b is then stored in the system 124 and remains static.
The characterization system 124 then constructs the forward transform 125 at 216 as the summation of the functions for each transform 125a, 125b for each of the device independent color space L,a*,b*: $L (CMYK) = f_{L, surf} (CMYK) + f_{L, residual} (CMYK);$
$a * (CMYK) = f_{a *, surf} (CMYK) + f_{a *, residual *} (CMYK);$
and $b * (CMYK) = f_{b *, surf} (CMYK) + f_{b *, residual} (CMYK),$
where the residual function f_residual is evaluated as a lookup table for points on the grid and is evaluated by interpolation for points off the grid. The initial device characterization is thus completed at 216. It is noted that the onboard characterization system 124 may perform some or all of the initial characterization tasks as described above, or some or all these tasks may be performed by an external system.
Fig. 5 illustrates exemplary adaptation processing 300 by the characterization system 124 beginning at 302. In practice, the adaptation can be performed on each individual device 100 once every day during cycle-up time, or during customer printing jobs to obtain the adaptation set, preferably via an onboard characterization system 124 without requiring user intervention. The system 124 is provided with a C,M,Y,K input adaption data set 122b at 304 for updating/adapting the parametric transform 125a (f_L,surf, f_a*,surf, f_b*,surf ) for each individual color reproduction device 100. The input adaptation data set 122b is used to print adaptation patches at 304 (e.g., patch images 162 in Fig. 2), and these are scanned at 306 (using scanner 126) to generate a measured La*b* adaptation data set 124c (Fig. 6). The C,M,Y,K input adaptation data set 122b and the corresponding measured La*b* adaptation data set 124c (e.g., around 1500 values for each in one embodiment) are then fitted at 308 to generate an updated parametric forward color transform h_{a*b*, adapt surf} (CMYK) 125a = (f_{L, adapt surf} (CMYK); f_{a*, adapt surf} (CMYK); and f _{b*, adapt surf} (CMYK). The overall forward transform (La*b*(CMYK)) 125 is updated at 310: $L (CMYK) = f_{L, adapt surf} (CMYK) + f_{L, residual} (CMYK);$
$a * (CMYK) = f_{a *, adapt surf} (CMYK) + f_{a *, residual *} (CMYK);$
and $b * (CMYK) = f_{b *, adapt surf} (CMYK) + f_{b *, residual} (CMYK) .$
The above described examples are merely illustrative of several possible embodiments of the present disclosure, wherein equivalent alterations and/or modifications will occur to others skilled in the art upon reading and understanding this specification and the annexed drawings. In particular regard to the various functions performed by the above described components (assemblies, devices, systems, circuits, and the like), the terms (including a reference to a "means") used to describe such components are intended to correspond, unless otherwise indicated, to any component, such as hardware, software, or combinations thereof, which performs the specified function of the described component (i.e., that is functionally equivalent), even though not structurally equivalent to the disclosed structure which performs the function in the illustrated implementations of the disclosure. In addition, although a particular feature of the disclosure may have been disclosed with respect to only one of several embodiments, such feature may be combined with one or more other features of the other implementations as may be desired and advantageous for any given or particular application. Also, to the extent that the terms "including", "includes", "having", "has", "with", or variants thereof are used in the detailed description and/or in the claims, such terms are intended to be inclusive in a manner similar to the term "comprising". It will be appreciated that various of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications, and further that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.

Claims

A method of characterizing a color reproduction device, the method comprising:
producing (10) a plurality of visible color images (162) using the color reproduction device (100) according to an input initial characterization data set (122a) in a first color space;

measuring (20) the color images (162) to generate a measured initial characterization data set (124a) in a second color space;

generating (32) a parametric forward color transform (125a) mapping color from the first color space to the second color space by fitting a polynomial surface to the measured initial characterization data set (122a) using the input initial characterization data set (122a) and the measured initial characterization data set (124a);

generating (34) an estimated initial characterization data set (124b) by evaluating values of the input initial characterization data set using the parametric forward color transform to generate the estimated initial characterization data set (124b)

generating (36) a nonparametric forward color transform (125b) by subtracting the estimated initial characterization data set values (124b) from the measured initial characterization data set values (124a) to determine residual difference values as said nonparametric forward color transform; and

constructing (40) a forward color transform (125) for the device (100) using the parametric (125a) and nonparametric (125b) forward color transforms.
The method of claim 1, wherein producing (10) the plurality of visible color images comprises printing a plurality of visible color patches using a printer, and wherein measuring (20) the color images comprises scanning the printed color patches to generate the measured initial characterization data set (124a).
The method of claim 1, wherein producing (10) the plurality of visible color images comprises rendering a plurality of visible color patches on a display.
The method of claim 1, wherein the input initial characterization data set (122a) is a four-dimensional data set with C,M,Y, and K values in the first color space, and wherein the measured (124a) and estimated (124b) initial characterization data sets are three-dimensional data sets with L,a*, and b* values in the second color space.
The method of claim 1, wherein the input initial characterization data set (122a) is homogeneously sampled with respect to a regular grid in the first color space.
The method of claim 5, wherein for any value in the first color space which is not on the grid, the residual difference values are determined using a distance-averaged interpolation technique using immediate neighbors in the input initial characterization data set (122a).
The method of claim 1, wherein the forward color transform for the device is constructed as a summation of the parametric (125a) and nonparametric (125b) forward color transforms.
The method of claim 1, further comprising adapting the parametric forward color transform (125a),
wherein adapting the parametric forward color transform comprises:
producing a plurality of visible adaptation images using the color reproduction device according to an input adaptation data set (122b) in the first color space;

measuring the adaptation images to generate a measured adaptation data set (124d) in the second color space; and

adapting the parametric forward color transform (125a) using the input adaptation data set (122b) and the measured adaptation data set (125c).
The method of claim 8, wherein producing the plurality of visible adaptation images comprises printing a plurality of visible adaptation patches using a printer according to the input adaptation data set (122b), and wherein measuring the adaptation images comprises scanning the printed adaptation patches using an in-line scanner of the printer to generate the measured adaptation data set (124c).
The method of claim 8, wherein adapting the parametric forward color transform (125a) comprises fitting a polynomial surface to the input adaptation data set (122b).
A color processing device, comprising:
a rendering system operative to produce a visible image according to input color data in a first color space;

a system controller operative to provide the input color data to the rendering system according to a print job;

a sensor operative to generate measured data in a second color space representative of the visible image; and

a characterization system coupled with the system controller and the sensor and operative:
to cause the rendering system to produce a plurality of visible color images according to an input initial characterization data set,

to receive a measured initial characterization data set representative of the color images from the sensor,

to generate a parametric forward color transform by fitting a polynomial surface to the measured initial characterization data set (122a) using the input initial characterization data set and the measured initial characterization data set,

to generate an estimated initial characterization data set by evaluating values of the input initial characterization data set using the parametric forward color transform to generate the estimated initial characterization data set (124b)

to generate a nonparametric forward color transform) by subtracting the estimated initial characterization data set values (124b) from the measured initial characterization data set values (124a) to determine residual difference values as said nonparametric forward color transform; and

to construct a forward color transform for the device using the parametric and nonparametric forward color transforms,
The color processing device of claim 11, wherein the rendering system comprises a plurality of marking devices operative according to the input initial characterization color data to transfer marking material onto a corresponding medium to create visible color images on the medium, and wherein the sensor is a scanner operative to scan the medium and to generate measured initial characterization data representative of the printed visible color images.
The color processing device of claim 12, wherein the characterization system is operative to adapt the parametric forward color transform,
and further comprises:
means for producing a plurality of visible adaptation images using the color reproduction device according to an input adaptation data set (122b) in the first color space;

means for measuring the adaptation images to generate a measured adaptation data set (124d) in the second color space; and

means for adapting the parametric forward color transform (125a) using the input adaptation data set (122b) and the measured adaptation data set (125c).